Slider questions… how useful are they and how should they be used?
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Slider questions are constructed to provide the survey-taker with a continuous scale upon which they can place themselves, rather than being forced into categories or checking boxes. It has important uses for data analysis as well, but before I talk about that in more detail, consider this:

“A Visual Analogue Scale (VAS) is a measurement instrument that tries to measure a characteristic or attitude that is believed to range across a continuum of values and cannot easily be directly measured. For example, the amount of pain that a patient feels ranges across a continuum from none to an extreme amount of pain. From the patient's perspective this spectrum appears continuous – their pain does not take discrete jumps, as a categorization of none, mild, moderate and severe would suggest. It was to capture this idea of an underlying continuum that the VAS was devised.” (Crighton, 2001)

VAS is used by medical professionals around the world and is proven to provide a clearer idea of a patients pain or discomfort (which is always relative) than previous systems where they fit into categories or steps of pain. Slider questions work the same way but instead of judging pain (probably best left to medical professionals) you are judging perceptions and attitudes.

So… when you are using slider questions then you are intelligently using survey question types in order to recreate a Visual Analogue Scale to capture survey-taker’s real attitudes and perceptions. How awesome are you? Pretty awesome, actually when you think about it. This is especially true if you also use complimentary questions to relativize these perceptions to optimize their usefulness for you.

There are a few important parameters to remember if you want to optimize the use of slider questions.

Second, you should keep the scale uniform throughout your survey. This will ward off confusion and ensure accurate results. This is also essential if you are to judge relative perceptions of survey-takers during data analysis. You will be able to get a more accurate absolute answer by allowing survey-takers to place themselves on a continuum rather than having to pick from categories such as ‘very much,’ ‘somewhat,’ ‘no opinion,’ ‘ not really,’ and ‘not at all.’ During data analysis you will be able to get more accurate averages of where people place themselves, rather than having a general category statistic average.

Third, compliment slider questions with other types of questions. Slider questions can sometimes become tedious for the survey-taker, so avoid putting too many of them in a row.

Fourth, when using verbal continuums choose the wording for the extremes of your spectrum carefully. If one side says ‘Very often’ then then opposite side should probably not say ‘Apples’… that would be just silly, not to mention confusing. Make sure these extremes makes sense vis-à-vis each other and that they are far enough apart to allow the survey-taker to feel there really is a choice in the continuum.

Constructing a slider question also makes it possible to take into account a variety of options:

Your slider question can have a numerical value, rather than wording at either extreme. You can scale it from 0 to 10, 1 to 3, 0 to 100, and so on… you have to possibility to play with the numbers. For example, creating a scale from 1 to 6 makes it so that there is no middle ground and therefore the survey-taker has to have a rather positive or rather negative view, you don’t allow them to take a neutral stance.

You can use emoticons at the extremes of your spectrum to limit biases created by misinterpretations or misunderstandings of extremes. :)

You also have options with respect to the slider’s cursor. You can adjust its starting position. This can be a useful tool. The middle of your spectrum is not always neutral. For example, if you have a numbered slider from 0 to 10 then the centre number is 5, which is not neutral. By giving it a value, this starting point could affect the way in which people respond to your question. In this case it may improve the quality of your results if the starting point of the cursor is at zero. There is also a decision to be made as to whether or not the actual numerical position of the cursor along the continuum should be shown to the survey-taker or not (especially in cases with large gaps like 0 to 100, is it important to know the survey-taker chose 79 and not 80?).

With slider questions, if the survey-taker does not touch the slider and simply goes on to the next question the answer does not register. With check-box style continuum questions it is not always possible to uncheck an answer once it has been checked, if the respondent checked the wrong box by mistake this can be a problem.

When using slider type questions as a ranking matrix question you are more likely to get accurate results than with check-box style continuum questions. This is because the check-box type ranking questions essentially create a confusing grid of squares (or circles) on the page, the survey-taker has to then click on a box from each line, and this often leads to ‘column-clicking.’ By this I mean that the survey-taker just clicks down the neutral column, or clicks randomly, because it is less of a hassle and the questions are in a confusing format anyway. With slider questions they cannot just click down the column, so you are more likely to get more accurate results.

Also, using sliders allows you to assess relative perception during data analysis. They allow you to not only see “the” average, but also “his” or “her” average. This could turn out to be incredibly important in analysing your results. Some people consistently answer harshly, while others consistently answer positively. In their evaluation it is helpful to keep relativity in mind. Here’s an example using a salary/work conditions assessment type survey sent out to all the workers of a company. The overall average on the question of salary contentment turned out to be 4 out of 10 (“the” average). This would normally indicate a low overall contentment. However, if we look closer at the surveys there could be other factors coming into play. Looking at one of the respondents survey answers we discover that though she marked 4 for salary contentment (“her” average), on every other question she consistently marked 1s or 2s. This is enlightening because it means that though her overall assessment of work conditions are indeed poor, salary-wise she feel relatively positive. This is obviously one respondents relative positioning, but it is possible to have a group of people who answer relatively harshly with a fair amount of consistency, which would mean you have to relativize your results during data analysis.

Slider questions are a versatile question type that, when used intelligently, can improve not only your survey itself and its results, but will also improve and fine-tune your data analysis. Use it well.